A comparative review of estimates of the proportion unchanged genes and the false discovery rate

Background  

In the analysis of microarray data one generally produces a vector of p-values that for each gene give the likelihood of obtaining equally strong evidence of change by pure chance. The distribution of these p-values is a mixture of two components corresponding to the changed genes and the unchanged ones. The focus of this article is how to estimate the proportion unchanged and the false discovery rate (FDR) and how to make inferences based on these concepts. Six published methods for estimating the proportion unchanged genes are reviewed, two alternatives are presented, and all are tested on both simulated and real data. All estimates but one make do without any parametric assumptions concerning the distributions of the p-values. Furthermore, the estimation and use of the FDR and the closely related q-value is illustrated with examples. Five published estimates of the FDR and one new are presented and tested. Implementations in R code are available.     

Regularized estimation of large-scale gene association networks using graphical Gaussian models

Background  

Graphical Gaussian models are popular tools for the estimation of (undirected) gene association networks from microarray data. A key issue when the number of variables greatly exceeds the number of samples is the estimation of the matrix of partial correlations. Since the (Moore-Penrose) inverse of the sample covariance matrix leads to poor estimates in this scenario, standard methods are inappropriate and adequate regularization techniques are needed. Popular approaches include biased estimates of the covariance matrix and high-dimensional regression schemes, such as the Lasso and Partial Least Squares.     

Down-regulation of the M6P/IGF-II receptor increases cell proliferation and reduces apoptosis in neonatal rat cardiac myocytes

Background  

The mannose 6-phosphate/insulin-like growth factor-II receptor (M6P/IGF2R) is a multi-functional protein that has been implicated in regulation of cell growth and apoptosis. Cardiac myocytes express relatively high levels of M6P/IGF2R, and cardiomyocyte apoptosis has been identified in a variety of cardiovascular disorders, such as myocardial infarction and heart failure. However, involvement of M6P/IGF2R in the pathogenesis of these conditions has not been determined. Thus, the objective of this study was to determine the role of M6P/IGF2R in regulation of cardiac myocyte growth and apoptosis.     

Local conservation scores without a priori assumptions on neutral substitution rates

Background  

Comparative genomics aims to detect signals of evolutionary conservation as an indicator of functional constraint. Surprisingly, results of the ENCODE project revealed that about half of the experimentally verified functional elements found in non-coding DNA were classified as unconstrained by computational predictions. Following this observation, it has been hypothesized that this may be partly explained by biased estimates on neutral evolutionary rates used by existing sequence conservation metrics. All methods we are aware of rely on a comparison with the neutral rate and conservation is estimated by measuring the deviation of a particular genomic region from this rate. Consequently, it is a reasonable assumption that inaccurate neutral rate estimates may lead to biased conservation and constraint estimates.     

BED estimates of HIV incidence: resolving the differences, making things simpler

Objective

Develop a simple method for optimal estimation of HIV incidence using the BED capture enzyme immunoassay.

Design

Use existing BED data to estimate mean recency duration, false recency rates and HIV incidence with reference to a fixed time period, T.

Methods

Compare BED and cohort estimates of incidence referring to identical time frames. Generalize this approach to suggest a method for estimating HIV incidence from any cross-sectional survey.

Results

Follow-up and BED analyses of the same, initially HIV negative, cases followed over the same set time period T, produce estimates of the same HIV incidence, permitting the estimation of the BED mean recency period for cases who have been HIV positive for less than T. Follow-up of HIV positive cases over T, similarly, provides estimates of the false-recent rate appropriate for T. Knowledge of these two parameters for a given population allows the estimation of HIV incidence during T by applying the BED method to samples from cross-sectional surveys. An algorithm is derived for providing these estimates, adjusted for the false-recent rate. The resulting estimator is identical to one derived independently using a more formal mathematical analysis. Adjustments improve the accuracy of HIV incidence estimates. Negative incidence estimates result from the use of inappropriate estimates of the false-recent rate and/or from sampling error, not from any error in the adjustment procedure.

Conclusions

Referring all estimates of mean recency periods, false-recent rates and incidence estimates to a fixed period T simplifies estimation procedures and allows the development of a consistent method for producing adjusted estimates of HIV incidence of improved accuracy. Unadjusted BED estimates of incidence, based on life-time recency periods, would be both extremely difficult to produce and of doubtful value.     

Branch length estimation and divergence dating: estimates of error in Bayesian and maximum likelihood frameworks

Background  

Estimates of divergence dates between species improve our understanding of processes ranging from nucleotide substitution to speciation. Such estimates are frequently based on molecular genetic differences between species; therefore, they rely on accurate estimates of the number of such differences (i.e. substitutions per site, measured as branch length on phylogenies). We used simulations to determine the effects of dataset size, branch length heterogeneity, branch depth, and analytical framework on branch length estimation across a range of branch lengths. We then reanalyzed an empirical dataset for plethodontid salamanders to determine how inaccurate branch length estimation can affect estimates of divergence dates.     

Evaluating concentration estimation errors in ELISA microarray experiments

Background  

Enzyme-linked immunosorbent assay (ELISA) is a standard immunoassay to estimate a protein's concentration in a sample. Deploying ELISA in a microarray format permits simultaneous estimation of the concentrations of numerous proteins in a small sample. These estimates, however, are uncertain due to processing error and biological variability. Evaluating estimation error is critical to interpreting biological significance and improving the ELISA microarray process. Estimation error evaluation must be automated to realize a reliable high-throughput ELISA microarray system.     

Child Mortality Estimation 2013: An Overview of Updates in Estimation Methods by the United Nations Inter-Agency Group for Child Mortality Estimation

Background

In September 2013, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) published an update of the estimates of the under-five mortality rate (U5MR) and under-five deaths for all countries. Compared to the UN IGME estimates published in 2012, updated data inputs and a new method for estimating the U5MR were used.

Methods

We summarize the new U5MR estimation method, which is a Bayesian B-spline Bias-reduction model, and highlight differences with the previously used method. Differences in UN IGME U5MR estimates as published in 2012 and those published in 2013 are presented and decomposed into differences due to the updated database and differences due to the new estimation method to explain and motivate changes in estimates.

Findings

Compared to the previously used method, the new UN IGME estimation method is based on a different trend fitting method that can track (recent) changes in U5MR more closely. The new method provides U5MR estimates that account for data quality issues. Resulting differences in U5MR point estimates between the UN IGME 2012 and 2013 publications are small for the majority of countries but greater than 10 deaths per 1,000 live births for 33 countries in 2011 and 19 countries in 1990. These differences can be explained by the updated database used, the curve fitting method as well as accounting for data quality issues. Changes in the number of deaths were less than 10% on the global level and for the majority of MDG regions.

Conclusions

The 2013 UN IGME estimates provide the most recent assessment of levels and trends in U5MR based on all available data and an improved estimation method that allows for closer-to-real-time monitoring of changes in the U5MR and takes account of data quality issues.     

Mutation accumulation in <Emphasis Type="Italic">Tetrahymena</Emphasis>

Background  

The rate and fitness effects of mutations are key in understanding the evolution of every species. Traditionally, these parameters are estimated in mutation accumulation experiments where replicate lines are propagated in conditions that allow mutations to randomly accumulate without the purging effect of natural selection. These experiments have been performed with many model organisms but we still lack empirical estimates of the rate and effects of mutation in the protists.     

FCI: an R-based algorithm for evaluating uncertainty of absolute real-time PCR quantification

Background  

FCI is an R code for analyzing data from real-time PCR experiments. This algorithm estimates standard curve features as well as nucleic acid concentrations and confidence intervals according to Fieller's theorem.     

RankAggreg, an R package for weighted rank aggregation

Background

Determining the parameters of a mathematical model from quantitative measurements is the main bottleneck of modelling biological systems. Parameter values can be estimated from steady-state data or from dynamic data. The nature of suitable data for these two types of estimation is rather different. For instance, estimations of parameter values in pathway models, such as kinetic orders, rate constants, flux control coefficients or elasticities, from steady-state data are generally based on experiments that measure how a biochemical system responds to small perturbations around the steady state. In contrast, parameter estimation from dynamic data requires time series measurements for all dependent variables. Almost no literature has so far discussed the combined use of both steady-state and transient data for estimating parameter values of biochemical systems.

Results

In this study we introduce a constrained optimization method for estimating parameter values of biochemical pathway models using steady-state information and transient measurements. The constraints are derived from the flux connectivity relationships of the system at the steady state. Two case studies demonstrate the estimation results with and without flux connectivity constraints. The unconstrained optimal estimates from dynamic data may fit the experiments well, but they do not necessarily maintain the connectivity relationships. As a consequence, individual fluxes may be misrepresented, which may cause problems in later extrapolations. By contrast, the constrained estimation accounting for flux connectivity information reduces this misrepresentation and thereby yields improved model parameters.

Conclusion

The method combines transient metabolic profiles and steady-state information and leads to the formulation of an inverse parameter estimation task as a constrained optimization problem. Parameter estimation and model selection are simultaneously carried out on the constrained optimization problem and yield realistic model parameters that are more likely to hold up in extrapolations with the model.     

A genetic dissection of the LlaJI restriction cassette reveals insights on a novel bacteriophage resistance system

Background  

Restriction/modification systems provide the dual function of protecting host DNA against restriction by methylation of appropriate bases within their recognition sequences, and restriction of foreign invading un-methylated DNA, such as promiscuous plasmids or infecting bacteriphage. The plasmid-encoded LlaJI restriction/modification system from Lactococcus lactis recognizes an asymmetric, complementary DNA sequence, consisting of 5'GACGC'3 in one strand and 5'GCGTC'3 in the other and provides a prodigious barrier to bacteriophage infection. LlaJI is comprised of four similarly oriented genes, encoding two 5mC-MTases (M1.LlaJI and M2.LlaJI) and two subunits responsible for restriction activity (R1.LlaJI and R2.LlaJI). Here we employ a detailed genetic analysis of the LlaJI restriction determinants in an attempt to characterize mechanistic features of this unusual hetero-oligomeric endonuclease.     

Child Mortality Estimation: Appropriate Time Periods for Child Mortality Estimates from Full Birth Histories

Background

Child mortality estimates from complete birth histories from Demographic and Health Surveys (DHS) surveys and similar surveys are a chief source of data used to track Millennium Development Goal 4, which aims for a reduction of under-five mortality by two-thirds between 1990 and 2015. Based on the expected sample sizes when the DHS program commenced, the estimates are usually based on 5-y time periods. Recent surveys have had larger sample sizes than early surveys, and here we aimed to explore the benefits of using shorter time periods than 5 y for estimation. We also explore the benefit of changing the estimation procedure from being based on years before the survey, i.e., measured with reference to the date of the interview for each woman, to being based on calendar years.

Methods and Findings

Jackknife variance estimation was used to calculate standard errors for 207 DHS surveys in order to explore to what extent the large samples in recent surveys can be used to produce estimates based on 1-, 2-, 3-, 4-, and 5-y periods. We also recalculated the estimates for the surveys into calendar-year-based estimates. We demonstrate that estimation for 1-y periods is indeed possible for many recent surveys.

Conclusions

The reduction in bias achieved using 1-y periods and calendar-year-based estimation is worthwhile in some cases. In particular, it allows tracking of the effects of particular events such as droughts, epidemics, or conflict on child mortality in a way not possible with previous estimation procedures. Recommendations to use estimation for short time periods when possible and to use calendar-year-based estimation were adopted in the United Nations 2011 estimates of child mortality.     

Distance Estimation Is Influenced by Encoding Conditions

Background

It is well established that foveating a behaviorally relevant part of the visual field improves localization performance as compared to the situation where the gaze is directed elsewhere. Reduced localization performance in the peripheral encoding conditions has been attributed to an eccentricity-dependent increase in positional uncertainty. It is not known, however, whether and how the foveal and peripheral encoding conditions can influence spatial interval estimation. In this study we compare observers'' estimates of a distance between two co-planar dots in the condition where they foveate the two sample dots and where they fixate a central dot while viewing the sample dots peripherally.

Methodology/Principal Findings

Observers were required to reproduce, after a short delay, a distance between two sample dots based on a stationary reference dot and a movable mouse pointer. When both sample dots are foveated, we find that the distance estimation error is small but consistently increases with the dots-separation size. In comparison, distance judgment in peripheral encoding condition is significantly overestimated for smaller separations and becomes similar to the performance in foveal trials for distances from 10 to 16 degrees.

Conclusions/Significance

Although we find improved accuracy of distance estimation in the foveal condition, the fact that the difference is related to the reduction of the estimation bias present in the peripheral conditon, challenges the simple account of reducing the eccentricity-dependent positional uncertainty. Contrary to this, we present evidence for an explanation in terms of neuronal populations activated by the two sample dots and their inhibitory interactions under different visual encoding conditions. We support our claims with simulations that take into account receptive fields size differences between the two encoding conditions.     

Antimicrobial breakpoint estimation accounting for variability in pharmacokinetics

Background  

Pharmacokinetic and pharmacodynamic (PK/PD) indices are increasingly being used in the microbiological field to assess the efficacy of a dosing regimen. In contrast to methods using MIC, PK/PD-based methods reflect in vivo conditions and are more predictive of efficacy. Unfortunately, they entail the use of one PK-derived value such as AUC or Cmax and may thus lead to biased efficiency information when the variability is large. The aim of the present work was to evaluate the efficacy of a treatment by adjusting classical breakpoint estimation methods to the situation of variable PK profiles.     

Estimating pneumonia deaths of post-neonatal children in countries of low or no death certification in 2008

Background

Pneumonia is the leading cause of child deaths globally. The aims of this study were to: a) estimate the number and global distribution of pneumonia deaths for children 1–59 months for 2008 for countries with low (<85%) or no coverage of death certification using single-cause regression models and b) compare these country estimates with recently published ones based on multi-cause regression models.

Methods and Findings

For 35 low child-mortality countries with <85% coverage of death certification, a regression model based on vital registration data of low child-mortality and >85% coverage of death certification countries was used. For 87 high child-mortality countries pneumonia death estimates were obtained by applying a regression model developed from published and unpublished verbal autopsy data from high child-mortality settings. The total number of 1–59 months pneumonia deaths for the year 2008 for these 122 countries was estimated to be 1.18 M (95% CI 0.77 M–1.80 M), which represented 23.27% (95% CI 17.15%–32.75%) of all 1–59 month child deaths. The country level estimation correlation coefficient between these two methods was 0.40.

Interpretation

Although the overall number of post-neonatal pneumonia deaths was similar irrespective to the method of estimation used, the country estimate correlation coefficient was low, and therefore country-specific estimates should be interpreted with caution. Pneumonia remains the leading cause of child deaths and is greatest in regions of poverty and high child-mortality. Despite the concerns about gender inequity linked with childhood mortality we could not estimate sex-specific pneumonia mortality rates due to the inadequate data. Life-saving interventions effective in preventing and treating pneumonia mortality exist but few children in high pneumonia disease burden regions are able to access them. To achieve the United Nations Millennium Development Goal 4 target to reduce child deaths by two-thirds in year 2015 will require the scale-up of access to these effective pneumonia interventions.     

Phylogeny of Mycobacterium tuberculosis Beijing strains constructed from polymorphisms in genes involved in DNA replication, recombination and repair

Background

The Beijing family is a successful group of M. tuberculosis strains, often associated with drug resistance and widely distributed throughout the world. Polymorphic genetic markers have been used to type particular M. tuberculosis strains. We recently identified a group of polymorphic DNA repair replication and recombination (3R) genes. It was shown that evolution of M. tuberculosis complex strains can be studied using 3R SNPs and a high-resolution tool for strain discrimination was developed. Here we investigated the genetic diversity and propose a phylogeny for Beijing strains by analyzing polymorphisms in 3R genes.

Methodology/Principal Findings

A group of 3R genes was sequenced in a collection of Beijing strains from different geographic origins. Sequence analysis and comparison with the ones of non-Beijing strains identified several SNPs. These SNPs were used to type a larger collection of Beijing strains and allowed identification of 26 different sequence types for which a phylogeny was constructed. Phylogenetic relationships established by sequence types were in agreement with evolutionary pathways suggested by other genetic markers, such as Large Sequence Polymorphisms (LSPs). A recent Beijing genotype (Bmyc10), which included 60% of strains from distinct parts of the world, appeared to be predominant.

Conclusions/Significance

We found SNPs in 3R genes associated with the Beijing family, which enabled discrimination of different groups and the proposal of a phylogeny. The Beijing family can be divided into different groups characterized by particular genetic polymorphisms that may reflect pathogenic features. These SNPs are new, potential genetic markers that may contribute to better understand the success of the Beijing family.     

CoXpress: differential co-expression in gene expression data

Background  

Traditional methods of analysing gene expression data often include a statistical test to find differentially expressed genes, or use of a clustering algorithm to find groups of genes that behave similarly across a dataset. However, these methods may miss groups of genes which form differential co-expression patterns under different subsets of experimental conditions. Here we describe coXpress, an R package that allows researchers to identify groups of genes that are differentially co-expressed.     

The effect of reference sample composition and size on dental age interval estimates

Objectives

Validation studies in juvenile dental age estimation primarily focus on point estimates while interval performance for reference samples of different ancestry group compositions has received minimal attention. We tested the effect of reference sample size and composition by sex and ancestry group on age interval estimates.

Materials and Methods

The dataset consisted of Moorrees et al. dental scores from panoramic radiographs of 3334 London children of Bangladeshi and European ancestry and 2–23 years of age. Model stability was assessed using standard error of mean age-at-transition for univariate cumulative probit and sample size, group mixing (sex or ancestry), and staging system as factors. Age estimation performance was tested using molar reference samples of four sizes, stratified by year of age, sex, and ancestry. Age estimates were performed using Bayesian multivariate cumulative probit with 5-fold cross-validation.

Results

Standard error increased with decreasing sample size but showed no effect from mixing by sex or ancestry. Estimating ages using a reference and target sample of different sex reduced success rate significantly. The same test by ancestry groups had a lesser effect. Small sample size (n < 20/year of age) negatively affected most performance metrics.

Discussion

We found that reference sample size, followed by sex, primarily drove age estimation performance. Combining reference samples by ancestry produced equivalent or better estimates of age by all metrics than using a single-demographic reference of smaller size. We further proposed that population specificity is an alternative hypothesis of intergroup difference that has been erroneously treated as a null.